Question

我在Power BI中有大量原始故障数据。

code    time                    status  
x123    2019-04-22T23:57:00     ok  
x123    2019-04-23T01:00:00     faulty  
x123    2019-04-23T02:00:00     ok  
x123    2019-04-23T23:00:00     faulty  
x123    2019-04-24T01:00:00     ok

我需要对此进行转换，以显示某项产品在给定日期处于错误状态多长时间了。因此，在23日，该商品在下午1点至2点之间处于故障状态，然后在晚上11点之间再次出现故障，直到深夜。

code    day         % of day faulty  
x123    23/04/2019  8.30%           (2 hours)

我可以在Power BI中轻松做到这一点吗，还是应该使用其他工具（例如Azure数据工厂）？

Answer 1

将以下计算列添加到表中：

Report Date = Table1[time].[Date]

Fault Duration = 
VAR CurrentTime = Table1[time]
VAR CurrentCode = Table1[code]
VAR PreviousTime = 
    CALCULATE ( 
        MAX ( Table1[time] ),
        FILTER ( 
            Table1,
            Table1[time] < CurrentTime && 
            Table1[code] = CurrentCode
        )
    )
VAR NextTime = 
    CALCULATE ( 
        MIN ( Table1[time] ),
        FILTER ( 
            Table1,
            Table1[time] > CurrentTime && 
            Table1[code] = CurrentCode
        )
    )
VAR FaultyFrom = 
    IF(
        Table1[status] = "faulty",
        Table1[time],
        IF (
            DAY(PreviousTime) = DAY(Table1[time]),
            BLANK(),
            Table1[time].[Date]
        )
    )
VAR FaultyTo = 
    IF ( 
        Table1[status] = "ok",
        Table1[time],
        IF (
            DAY(NextTime) = DAY(Table1[time]),
            NextTime,
            Table1[time].[Date] + 1
        )
    )
RETURN
    IF(
        ISBLANK ( PreviousTime ) || ISBLANK ( NextTime ) || ISBLANK ( FaultyFrom ),
        BLANK(),
        FaultyTo - FaultyFrom
    )

现在创建度量：

Faulty Hours = SUM ( Table1[Fault Duration] )

Faulty % Day = 
    IF ( 
        HASONEVALUE ( Table1[Report Date] ),
        DIVIDE ( 
            [Faulty Hours],
            DISTINCTCOUNT ( Table1[code] ),
            BLANK()
        ),
        BLANK()
    )

输出：

有关有效的PBIX文件示例，请参见https://pwrbi.com/so_55825688/

数据转换的工具推荐

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